The goal of this project is to develop and apply improved statistical methods for human fertility studies. Work has progressed in the development of statistical models that (1) distinguish covariate effects on the average level of fertility from effects on the duration of the fertile window, and (2) characterize heterogeneity among menstrual cycles and women with respect to surrogates of fertility. We have applied the first approach to assess declines with male and female age in the level and duration of fertility in the menstrual cycle. We have also used the approach to assess relationships between cervical mucus characteristics and fertility. In the second area, we developed a Bayesian model that incorporates prior information in estimating patterns of cervical mucus secretions in the menstrual cycle. This model was used to demonstrate consistency across cycles from a women in the trajectory of cervical mucus secretions on different days in the fertile interval.